Industrial control energy object

ABSTRACT

An energy object extension to an industrial protocol having a comprehensive suite of attributes, messages and services utilized for the monitoring and control of energy consuming or producing resources by a manufacturing automation application is provided. The energy object includes an identifier associated with an energy resource that is associated with a manufacturing automation application and an energy type associated with the energy resource. This includes a measurement characteristic associated with the energy resource to facilitate energy management by the manufacturing automation application.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 12/684,469, entitled “Industrial Control Energy Object”, filedJan. 8, 2010, which is herein incorporated by reference.

BACKGROUND

The claimed subject matter relates generally to industrial controlsystems and more particularly to control of power and energy thatenables efficient and automated management of the same across variouscommunications networks.

Various industrial protocols are employed to support automatedmanufacturing operations and communications. These can include deviceprotocols, mid-level protocols between the device level and the controllevel, and upper-level protocols such as Ethernet that has been adaptedto communicate via industrial control objects among factories and on tohigh-level networks such as the Internet. In one specific example ofsuch an industrial protocol, the Common Industrial Protocol (CIP™)encompasses a comprehensive suite of attributes, messages and services,organized as objects, for the enablement of manufacturing automationapplication objectives—control, safety, synchronization, motion,configuration and information collection. Further, it enables users tointegrate these manufacturing applications with enterprise-levelEthernet networks and the Internet. Supported by hundreds of vendorsaround the world, CIP provides users with a unified communicationarchitecture throughout the manufacturing enterprise. The CIP protocolallows users to benefit today from the many advantages of open networkswhile protecting their existing automation investments when upgrading inthe future.

Through the addition of functionally specialized objects, the CIPprotocol provides a coherent integration of control, motion andsynchronization, configuration and diagnostics, and safety information.This protocol includes seamless bridging and routing without the addedcost and complexity of bridges and proxies. Further, the protocolprovides freedom to deploy interoperable, multivendor systems, allowingusers to choose best-of-breed products, with the assurance ofcompetitive prices and low integration cost. This includes single, mediaindependent protocol for all network adaptations of CIP—EtherNet/IP™,DeviceNet™, CompoNet™, and ControlNet™—that allows users to select thebest network or networks for their application while still minimizingtheir overall investment in system engineering, installation,integration and commissioning. The CIP protocol also integrates supportof Modbus® server devices into the CIP architectures with Modbustranslation services for originator devices on CIP; allows devicessupporting Modbus TCP and EtherNet/IP to reside on the same TCP/IPnetwork—or even in the same device. Modbus integration is accomplishedby the usage of objects to create an abstraction. Modbus is thenaccessed as if the Modbus devices were native CIP devices. It should berecognized that the functionality provided by a CIP object can beextended into other non-CIP networks in a similar manner.

A key topic that has gained prominence in modern industrialmanufacturing is the ability to efficiently manage power and energywithin a plant or across a set of plants and an associated supply chain,where such management spans a wide geography and communicates overnetworks. This includes the ability to understand and track in realtime, where energy is being generated, transmitted, distributed andutilized. For instance, Cap and Trade policies may have to be consideredin the management of a particular plant or even across broader energydomains that may be associated with a grid. Some of the energymanagement must be coordinated with the grid such as the ability toreceive energy from the grid or conversely return unused energy back tothe grid for appropriate credit. Unfortunately, existing industrialprotocols do not support a standardized ability to aggregate energy dataor manage energy resources let alone communicate or facilitate controlin even the most basic energy demand applications. Presently, thedifficulty in automation due to the lack of uniform methods of energymanagement information exchange leads most often to a manual exercisethat is far from an efficient and responsive method for controlling andmanaging complex energy flows that dynamically change over time.

BRIEF DESCRIPTION

The following summary presents a simplified overview to provide a basicunderstanding of certain aspects described herein. This summary is notan extensive overview nor is it intended to identify critical elementsor delineate the scope of the aspects described herein. The sole purposeof this summary is to present some features in a simplified form as aprelude to a more detailed description presented later.

An energy object is provided that enables energy in all its forms to bemanaged automatically across industrial communication networks. Theenergy object includes the ability to aggregate energy data from variouspoint sources that may originate within a plant or more broadly acrossnetworks external to the plant that define an energy domain. This caninclude control devices that report energy that has been discretelytaken from or added to a grid such as a smart grid that credits usersfor efficient energy use and transfer with the respective grid. Byautomatically collating energy data within an industrial protocol viathe energy object and discrete energy monitoring sources, energy can beefficiently managed by associating its use to the actual production ofproducts or services that consume the energy or conversely produce it.By having discrete control and understanding of energy in its smallestor discrete form from numerous network locations, energy can becontrolled dynamically as a commodity to best serve variousapplications. Obvious applications include energy conservation wherenon-necessary components are idled or previously used processes areemployed to return unused energy to an external or internal grid. Morecomplex applications such as Cap & Trade and automated demand response(ADR) can easily employ energy objects as a control mechanism (e.g.,turn off or on an energy source) or as a collection mechanism todetermine and demonstrate that the energy users are in compliance.

In one aspect, the energy object can include an identifier having adevice name, a qualified hierarchy, and an object class for associatinga process with an energy source. The object can specify the type ofenergy consumed such as water, air, gas, electricity and steam (WAGES),for example. This can include measurements, some type of aggregation,and some type of time reference among other parameters. Water, forexample, can be used to move materials and provide heating and cooling.Also, considering provision by utilities and climate and geographyrelated usage limitations, it should be apparent that it is reasonableto manage water in an analogous manner as electricity. In anotheraspect, an energy object extension to an industrial protocol having acomprehensive suite of attributes, messages and services utilized forthe monitoring and control of energy consuming or producing resources bya manufacturing automation application is provided. The energy objectincludes an identifier associated with an energy resource that isassociated with a manufacturing automation application and an energytype associated with the energy resource. This includes a measurementcharacteristic associated with the energy resource to facilitate energymanagement by the manufacturing automation application.

To the accomplishment of the foregoing and related ends, the followingdescription and annexed drawings set forth in detail certainillustrative aspects. These aspects are indicative of but a few of thevarious ways in which the principles described herein may be employed.Other advantages and novel features may become apparent from thefollowing detailed description when considered in conjunction with thedrawings.

DRAWINGS

These and other features, aspects, and advantages of the presentinvention will become better understood when the following detaileddescription is read with reference to the accompanying drawings in whichlike characters represent like parts throughout the drawings, wherein:

FIG. 1 is a schematic block diagram illustrating industrial energyobjects for controlling energy processes.

FIG. 2 is a diagram illustrating communications of energy objects tohigher level systems.

FIG. 3 is an example set of parameters that can be employed with anenergy object.

FIG. 4 is an example device model that illustrates energy object usageat the device level.

FIG. 5 is a diagram illustrating an example controller informationmodel.

FIG. 6 is a diagram illustrating an example batch energy model.

FIG. 7 illustrates an example system for measuring and aggregatingenergy data.

FIG. 8 illustrates an example system for measuring energy duringexecution of an automated process.

FIG. 9 illustrates an example system depicting scheduling productionover multiple areas according to energy consumption.

FIG. 10 illustrates an example application for energy management of aproduct line.

FIG. 11 is a flow diagram illustrating an example energy managementprocess.

FIG. 12 is a schematic block diagram of a system including a higherlevel energy management system that interacts with a controllerconfigured to control operation of a plurality of field devices that, inturn, control a plurality of energy consuming or producing processes.

FIG. 13 is a schematic block diagram of the system of FIG. 12 includingan additional intelligent field device that includes an energy objectand controls an additional energy consuming or producing process.

FIG. 14 is a schematic diagram of the controller of FIGS. 12 and 13.

DETAILED DESCRIPTION

An energy object extension to an industrial protocol having acomprehensive suite of attributes, messages and services utilized forthe monitoring and control of energy consuming or producing resources bya manufacturing automation application is provided. The energy objectincludes an identifier associated with an energy resource that isassociated with a manufacturing automation application and an energytype associated with the energy resource. This includes a measurementcharacteristic associated with the energy resource to facilitate energymanagement by the manufacturing automation application.

Referring initially to FIG. 1, a system 100 illustrates industrialenergy objects for controlling energy processes an industrial automationenvironment. The system 100 includes a plurality of energy consuming orproducing energy sources 110 (also referred to as energy resources) thatare monitored by various controllers 120, where such controllers 120 caninclude components or modules that report to supervisory controllers orcomputer-based applications. For example, a historian component (notshown) may be employed in conjunction with the controller 120 to tag oridentify energy measurements associated with a location in an automatedprocess that is associated with the energy sources 110. The controllers120 create or use one or more energy objects 130 that provide protocolextensions to industrial automation protocols to enhance energymanagement capabilities of automation devices and software.Substantially any communication protocol can convey energy monitoringand control messages, where such enhancements are described in moredetail with respect to FIG. 3. For example, an Ethernet protocol can beenhanced to transport messages from energy objects 130 which in turn canbe employed to monitor energy consumption and/or control energy usage.

A basic communication protocol may be extended by layering an industrialcommunication protocol on top of the basic communication protocol. Forexample, Ethernet is extended for industrial control purposes bylayering the Common Industrial Protocol (CIP) on top of the InternetProtocol (IP) and this on top of Ethernet. Thus, CIP provides a methodto interact with the energy object that is independent of the underlyingcommunication protocols. As shown, higher level energy managementsystems and software 140 can employ the CIP protocol to interact withthe energy objects 130 in order to facilitate overall energycontrol/management of a factory or participate across a network andassociated grid with a collection of factories or processes. It shouldbe appreciated that energy objects 130 may reside in controller 120,higher level energy management system 140, or more commonly in separateintelligent field devices linked to the controller. The CIP protocolprovides transparent access in either case.

In general, the energy objects 130 enable energy in all its forms to bemanaged automatically across industrial communication networks. Theenergy object 130 includes the ability to aggregate energy data fromvarious point sources 110 that may originate within a plant or morebroadly across networks external to the plant that define an energydomain. This can include control devices 120 that report energy that hasbeen discretely taken from or added to a grid such as a smart grid (notshown) that credits users for efficient energy use and transfer with therespective grid. By automatically collating energy data within anindustrial protocol via the energy object 130 and discrete energymonitoring sources 120, energy can be efficiently managed by associatingits use to the actual production products or services that consume theenergy or conversely produce it. By having discrete control andunderstanding of energy in its smallest or discrete form from numerousdistributed network locations, energy can be controlled dynamically as acommodity to best serve various applications. Obvious applicationsinclude energy conservation where non-necessary components are idled orpreviously used processes are employed to return unused energy to thegrid. More complex applications such as Cap & Trade can easily becontrolled and monitored via the energy objects 130 that can also beemployed as a control mechanism (e.g., turn off or on an energy source)or employed as a reporting device to show companies are in compliance.

In one aspect, the energy object 130 can include an identifier having adevice name, a qualified hierarchy, and an object class for associatinga process with an energy source. The energy object 130 can specify thetype of energy consumed such as water, air, gas, electricity and steam,for example. This can include measurements, some type of aggregation,and some type of time reference among other parameters. In one aspect,an energy object extension to an industrial protocol is provided havinga comprehensive suite of attributes, messages and services for thecollection of manufacturing automation applications. The energy object130 includes an identifier associated with an energy consuming orproducing resource in a manufacturing automation application and anenergy type associated with the energy resource. This energy object alsoincludes a measurement characteristic associated with the energy typeamong other parameters described below with respect to FIG. 3 forcontrolling and monitoring the energy resource.

The energy objects 130 enable various aspects of control and monitoring.In one aspect, automated demand response (ADR) programs can be enabled.This allows consumers to automatically reduce usage to reduce peak gridload at utility request or at specific times while addressing energygeneration limits, transmission limits, and failures. Demand/responsecan include reducing the base load, sequencing start-up, and sheddingnon-critical loads. This also includes generating power, storing energyfor later usage, staggering power peaks, and operating at a reducedrate/capacity, for example.

The energy objects can be employed in conjunction with a Smart Grid torequest/demand to reduce or produce energy, bid exchange for reducing orproducing energy, control immediate needs or future consumption (e.g.,day ahead event scheduling), or utility measurement enforcement andsettlement. Within the confines of the plant, automated measurementsdetermine usage which can be employed to reduce lower production rates,re-schedule production, or shed loads, for example. Energy productioncan include re-use for the factory, supplying energy to the grid, andreceiving credits for excess power supplied to the grid.

Energy can be controlled via the energy objects 130 within theconstraints of existing safety control systems. Events should be arequest at the machine/cell, not a direct load control. Immediateshutdown of a load, without the proper prerequisite steps, may not besafe. Current event triggered load shedding may be able to occur with adelay to allow safe state controls. Future event load shedding can bescheduled to accommodate safety time. It is also noted that energy canbe managed, controlled, and computed in substantially any form. Thisincludes measurements that relate to energy (e.g., joules), voltage,current (real and reactive), power (e.g., joules/sec, volt*amps), fluidflows, pressure, temperature, and substantially any parameter ormeasurement that has some relationship to energy or power.

The energy objects 130 can also be employed to manage billing for usageincluding charging for the total kWh over a billing period. This may betiered in rate, changed by season, changed by time of day (on/off peak),and so forth. Electrical peak demand charges can include automatedcharging/billing for the highest average kW usage during any singledemand interval in the billing cycle. Demand intervals can includesubdivision of the billing cycle during which peak demand is measured.Intervals are typically a 15 or 30 minute period but other periods canbe employed. Intervals may be “rolling” or fixed to a time reference.Ratchet clauses can be supported that include increased peak demandcharges in subsequent billing cycles due to a high peak demand in aprior billing cycle. Reactive demand charges include usage at non-unitypower factor. The energy objects can also be employed with a safetycomponent (e.g., safety PLC to control switching to different energystates) that limits activation, deactivation or modulation of an energyconsuming or producing resource.

In one example application of the system 100, a manufacturing automationsystem for monitoring Cap and Trade emissions across multiple devicescommunicating within an industrial process can be provided. Thisincludes a set of objects having identifiers associated with a number ofemitting resources, an emission type, and a monitoring component tofacilitate measurement and recording of emissions from the resourceswithin the industrial process. This also includes a controller having anemission cap parameter set within a memory of the controller, where thecontroller processes the energy object. The system includes anaccumulation function operating with the controller and operativelycommunicating with the object to accumulate the emissions from theresources and calculate a total emission, compare with the capparameter, and provide notification for a trade if the cap is determinedto be increased. The manufacturing automation system can also include acomponent to increase the cap parameter by communication from thecontroller to an external source that facilitates the trade.

In another aspect various forecasting applications can be supported. Ahistorian type application can estimate a forward-looking forecast ofenergy use and demand based on a combination of energy data collectedthrough the energy object, historical production, environmental andother related data, production schedules, weather forecasts, and soforth. The forecast could be set up as one hour, one day, one week, onemonth ahead (with higher confidence factors the shorter the forecastperiod), and could be communicated through a “Smart Grid” portal toenergy providers to assist them in planning and controlling supply andhopefully passing along resulting efficiencies in the form of lowerenergy costs.

It is noted that components associated with the system 100 andcontrollers 120 can include various computer or network components suchas servers, clients, controllers, industrial controllers, programmablelogic controllers (PLCs), electric drives, energy monitors, batchcontrollers or servers, distributed control systems (DCS),communications modules, mobile computers, wireless components, controlcomponents and so forth that are capable of interacting across anetwork. Similarly, the term controller or PLC as used herein caninclude functionality that can be shared across multiple components,systems, or networks. For example, one or more controllers cancommunicate and cooperate with various network devices across thenetwork. This can include substantially any type of control,communications module, computer, I/O device, sensors, Human MachineInterface (HMI) that communicate via the network that includes control,automation, or public networks. The controller can also communicate toand control various other devices such as Input/Output modules includingAnalog, Digital, Programmed/Intelligent I/O modules, other programmablecontrollers, communications modules, sensors, output devices, and thelike. It is further noted that the industrial automation as describedherein can include substantially any type of manufacturing automationthat further includes all process and discrete manufacturing, as well asbuilding maintenance, for example.

The network can include public networks such as the Internet, Intranets,and automation networks such as Control and Information Protocol (CIP)networks including DeviceNet and ControlNet. Other networks includeEthernet, DH/DH+, Remote I/O, Fieldbus, Modbus, Profibus, wirelessnetworks, serial protocols, and so forth. In addition, the networkdevices can include various possibilities (hardware or softwarecomponents). These include components such as switches with virtuallocal area network (VLAN) capability, LANs, WANs, proxies, gateways,routers, firewalls, virtual private network (VPN) devices, servers,clients, computers, configuration tools, monitoring tools, or otherdevices.

Turning now to FIG. 2, an example system 200 illustrates communicationsof information between energy objects and higher level systems. Similarto FIG. 1, the system 200 includes a plurality of energy consuming orproducing energy sources 210 (also referred to as energy resources) thatare monitored by various controllers 220, where such controllers 220 caninclude components or modules that report to supervisory controllers orapplications. The controllers 220 embed or route access to one or moreenergy objects 230 that provide protocol extensions to industrialautomation protocols to enhance energy management capabilities ofautomation devices and software. As shown in this example, thecontrollers 220 can communicate with a Manufacturing Execution System(MES) 240 that participates in a shared database 250 with an EnergyManagement Control System (EMCS) 260. The MES 240 provides buildingcontrols 270 for energy management of building systems associated withthe automation systems under control of the MES 240. The EMCS 260 cancommunicate with a plurality of utilities at 280 that includes electric,water, and/or gas. The database 250 receives production schedulingrequests from Production Scheduling 290, an enterprise resource planning(ERP) system that creates a tentative schedule based on customer orders.The MES 240 system is responsible for the final execution of theschedule to fulfill the orders and has leeway to adjust the schedule inorder to manage automation system energy. Such fulfillment may includestaggering batch recipe step execution to minimize peak demand.

The energy objects 230 provide power and energy management extensionsfor devices in the system 200 and for processes controlled by respectivedevices. This enables manipulating discrete power modes, measuring totalenergy, and measuring demand (real and reactive), and provide alarm andevent messages on energy or power conditions. This also includesoptional generation control and optional diagnostic measurements thatincludes per phase and phase to phase currents and voltages in additionto trending, for example.

FIG. 3 illustrates an example set of parameters that can be employedwith an energy object previously described. It is noted that suchparameters are not an exhaustive set as other parameters can beprovided. At 310, an Identifier tags data to a related automation deviceor process. At 314, an Aggregation parameter provides paths toaggregated CIP objects that include sub-metering or ability to go tolower energy states (sequential turn-off). A role parameter 320identifies a source as a producer, consumer, or both. Another parameterincludes an Operational State 324 and yet another includes units/scalingfactors at 330 to specify accuracy. A Roll Over for Energy parameter isprovided at 334 in addition to a production capacity parameter at 340that includes continuous, stored, and load size (e.g.,W,VAR:electricity). At 344, Measurements include Instantaneous, Over aperiod, Negative values are producing, and so forth. At 350, a Typeparameter includes Water, Gas, Air, Steam, and Energy Quality, forexample. Energy quality may specify harmonic content, carbon generationrate or other factors related to a choice of energy sources duringoperation.

At 354, a Time reference parameter includes a time and date of theobject (r/w attribute). At 360 a Data log parameter can be provided tostore a set of measurements over a time period. At 364 a Priorityparameter includes Opt-out, critical, non-critical (Grid categories) andLoad shedding (Load-related) to assist in decision making in control ofthe energy resource. At 370, a Shed and Produce Services set includes arequest operation state change estimation, a response indicates time tochange operational state, and an actual request to change state. At 374,a CIP A&E (alarms & events) message set includes alarm on energyproduction below measured level (average or instantaneous) and alarm onenergy consumption above a measured level. As can be appreciated more orless parameters, services, or alarm and event messages than shown inFIG. 3 can be provided.

Referring to FIG. 4, an example device model illustrates energy objectusage at the device level. A device 400 includes interaction with othersystems such as configuration 404, messaging 406, and I/O exchange 408.The device 400 includes non-volatile storage 410 that holds variousparameter objects 420. The device 400 also includes various inputassembly objects 430 and output assembly objects 440. As shown, thedevice 400 can include an energy object instance at 450 or associatedexternal object instances at 460. The energy objects 450 and 460 can beintegrated providing controller access that is accessible on-demandthrough messaging that includes placing in tags by logic. The objectsare accessible via tags through I/O assembly objects 430 and 440. Energyrelated application logic can also be provided. Human Machine Interface(HMI) access includes OLE for Process Control (OPC) topics referencetags and Energy faceplates. Program access includes substantially anycommunications software that facilitates energy-specific programenhancements.

FIG. 5 illustrates an example controller information model 500. Themodel 500 includes a controller 510 that generates energy structuredtags 520 (or tags). The tags 520 can be exchanged with 3^(rd) partyenergy-enabled applications 530 via OPC topics 540 for example. The tags520 can also be communicated to an energy-enabled HMI 550 that candisplay various energy example aspects depicted at 560. The examples at560 that can be generated, communicated to other systems, and/ordisplayed include an energy resource name, a device name, an energystate, graphs or charts, demand charges, alarms or other eventinformation. As can be appreciated, other factory or control informationcan be displayed.

Referring to FIG. 6, an example batch energy model 600 is illustrated.The model 600 includes energy structured tags 610 that are processed bya controller 620. Such tags 610 can be updated via a predetermineddemand interval 630. The tags 610 can be employed with a sync signal 640to enable energy-enabled phase logic 650 that is controlled by asupervisory batch controller 660, where per recipe energy data or perphase energy data is exchanged. For batch and discrete controlapplications, equipment can be idled or shut down during non-productiontimes. In addition, the rate of production may be varied to reduceenergy consumption.

FIG. 7 illustrates example system 700 for measuring and aggregatingenergy data. The system 700 includes an energy database 710 (ordatabases) and associated software for collecting, displaying, andanalyzing energy object data. This can include collecting energy objectdata from one or more factory automation areas shown at 720 and 730. Thecollected energy data can be represented in the database 710 as an areamodel shown at 740 which represents the equipment or devices thatconsume or produce energy at discrete locations in a production process.The data can include raw measurements at 750 or processed measurementsat 760. Raw measurement data 750 can include an area name, equipmentname, time, measured power, or energy. Processed measurements caninclude in addition to area name and equipment name, average power andpeak power for example. As can be appreciated, a plurality of othercomputations and energy data can be processed or stored.

FIG. 8 illustrates an example system 800 for measuring energy duringexecution of an automated process. In this aspect, a production process810 triggers events 820 that cause energy data to be measured andcollected at 830 for each step in a production sequence. For instance,these events may enable a further measurement query and summing ofenergy data at 834, where the query returns the total energy required toproduce a specific product or production batch. As shown, the energy ismeasured from an area 840 but as noted previously, multiple areas can bemeasured within a factory or aggregated from across factories thatcommunicate via a network. At each stage shown at 850-870 of the process810 (or selected stages), events are generated at 820 to triggercollection of data at 830. As can be appreciated, discrete processes(non-batch or recipe) can similarly trigger energy data collection. Inthis aspect, production consumes energy at least partially in relationto the specific products. This enables per-phase energy measurementswhere phases are added for per product energy consumption. This providesthe basis for demand interval synchronization and demand measurement forproduct and batch phases or discrete assembly processes.

FIG. 9 illustrates another example system 900 depicting schedulingproduction over multiple areas according to energy consumption. Aprocess 910 starts area equipment that is enabled or disabled across anarea at 920 and/or an area at 930. In this example, the area 920 may bein a more automated area, provide lower lead time, have higher peakpower, utilize more per unit energy and so forth. The area 930 may be ina less automated area, provide higher lead time, have lower peak power,utilize less per unit energy and so forth. By monitoring the energyobjects from the respective areas 920 and 930, energy can be shiftedbetween areas to more efficiently utilize plant resources. As shown, anautomated production schedule 940 can initiate the process 910. Forexample, production can be scheduled to meet combined constraints ofdelivery before a deadline and reducing peak power in a future period.This could include building to inventory prior to deadline and futurereduced power period or delivering from inventory, building at a slowerrate in alternate with lower peak power, and/or rearranging parallelproduction so that power peaks are not concurrent.

FIG. 10 illustrates an example application system 1000 for energymanagement of product line 1010 (e.g., aluminum or steel production). Inthis aspect, the product line 1010 is regulated for average poweraccording to five minute periods at 1020. An electrical grid 1030 feedsthe line 1010 and is controlled by an automatic generator control 1040(AGC). Measurement devices are stationed on the power lines (e.g.,inductive or direct) at 1050, where data from the measurements areemployed in accordance with an energy object (not shown, describedabove). In this application, the system 1000 is enabled via the objectsto join energy markets as a regulation source and thus provide a gridservice. Regulation thus can provide a service where load current isbased on AGC signals from the grid and a process automatically modulatesload over a range while mitigating emissions, product degradation,and/or equipment damage.

It is noted that power quality load (phase) balancing applications canutilize an energy object in communicating power quality information andsending out alerts of fault conditions so that an energy consumer (e.g.,drives and rectifiers) can change their operating point to control powerfactor, or phase imbalance at the point of common coupling. Forinstance, a non-electrical example, in an air system, a secondcompressor could be signaled to turn on in the event of a leak, orprimary compressor failure. Thus, metering devices can be employed thatcan collect and trigger events. The events can be used by the energyobject to change the operating point of the device (e.g., drive) inother ways than to reduce energy consumption (power factor, phaseimbalance). This communication can be direct from device to device tofacilitate fastest action. In some applications, communication isperformed from the device monitoring energy, reporting to a controller.In other applications however, messages can be sent from device todevice (rather than through a controller) when it is advantageous to doso. It is also noted that when consumable resources are measured, theycan be included in the scope of the CIP energy object to provideenhanced forecasting. For example, measuring the solar intensity watertemperature, fuel oil levels or wind speed in addition to the electricalpower can be helpful in forecasting energy usage.

FIG. 11 is a flow diagram illustrating an example process 1100 forautomated energy management. While, for purposes of simplicity ofexplanation, the methodology is shown and described as a series of acts,it is to be understood and appreciated that the methodologies are notlimited by the order of acts, as some acts may occur in different ordersor concurrently with other acts from that shown and described herein.For example, those skilled in the art will understand and appreciatethat a methodology could alternatively be represented as a series ofinterrelated states or events, such as in a state diagram. Moreover, notall illustrated acts may be required to implement a methodology asdescribed herein.

Proceeding to 1110, one or more discrete energy sources are monitoredacross a network. These can include conventional sources such as gas orelectric or include more nuanced sources such as are described in moredetail below with respect to sustainability factors. At 1120, energydata is aggregated and subsequently communicated via one or more energyobjects as were previously described. Such objects can be employed toextend substantially any industrial protocol with energy monitoring andcontrol capability. At 1130, energy demands are determined from acrossthe network (or networks) from where the discrete energy sources werecollected. This can include determining whether systems or processshould be activated or deactivated to conserve and manage energyresources. As noted previously, a safety controller can be employed tofacilitate such activation and/or deactivation where some components onthe network may be activated while others are concurrently deactivated.At 1140, a determination is made as to whether or not energy should beautomatically adjusted up or down. This can include idling or reducingenergy in some processes and while activating or increasing energy insome others. If such adjustment is warranted, the process automaticallyadjusts energy supply or demand at 1160 before proceeding back to 1110and monitoring energy. If no such adjustment is required, the processproceeds back to 1110 from the decision at 1140.

FIG. 12 is a schematic block diagram of a system 1200 including a higherlevel energy management system 140 that interacts with a controller 120configured to control operation of a plurality of field devices 1202,1204 that, in turn, control a plurality of energy consuming or producingprocesses 110. Although illustrated in FIG. 12 as only including onehigher level energy management system 140, one controller 120, threefield devices 1202, 1204, and three energy consuming or producingprocesses 110, it will be understood that the system 1200 may insteadinclude any number of each of these components. As described above, theenergy objects 130 may be located in intelligent field devices 1202(i.e., field devices that are configured to compute energy usage for thefield device based on measured input/output process data and locallystored relationships between input/output process data values and energyusage), in controllers 120, or in higher level energy management systems140. For example, as illustrated in FIG. 12, the higher level energymanagement system 140 includes an energy object 130, the controller 120includes an energy object 130, and one of the intelligent field devices1202 includes an energy object. In certain embodiments, when the energyobject 130 is located outside of an intelligent field device 1202 (e.g.,the energy objects 130 located in the controller 120 or the higher levelenergy management system 140), the energy objects 130 may serve as aproxy for an intelligent field device 1202. Conversely, when anintelligent field device 1202 includes an energy object 130, the energyobject 130 contains the knowledge of how to measure energy usage and howto switch energy operation states (e.g., by switching to a low poweroperation state).

Not all field devices are intelligent field devices 1202 that containall of the knowledge necessary to measure energy usage and how to switchenergy operation states. However, using the energy objects 130 locatedin the higher level energy management system 140 and the controller 120illustrated in FIG. 12, a wider range of “non-intelligent” field devices1204 (i.e., field devices that are not configured to compute energyusage for the field device based on measured input/output process dataand locally stored relationships between input/output process datavalues and energy usage) may be incorporated into the controller 120 orinto the energy management system 140. In other words, there is thecapability to use energy objects 130 in other components of the system1200 as proxies for the field devices 1204, such that the field devices1204 are augmented to provide functionality similar to that of theintelligent field devices 1202. For example, the vast majority of fielddevices 1204 may not include energy objects 130. By allowing the energyobjects 130 to reside in a controller 120 associated with the fielddevices 1204, the controller 120 may utilize a proxy for the fielddevices 1204. Furthermore, some energy consuming or producing processes110 may be too complex to embed their energy knowledge into anassociated field device 1204. By allowing the energy objects 130 to belocated in a controller 120 associated with the energy consuming orproducing process 110 and/or the higher level energy management system140, which generally include greater processing power and resources,these complex energy consuming or producing process 110 may becontrolled with the same simple energy object interface.

Using the energy objects 130 in higher level energy management systems140 and controllers 120 as proxies for field devices 1204 includesapproximating energy usage for the field devices 1204 based on knowledgestored in the energy objects 130. For example, the energy object 130located in the controller 120 illustrated in FIG. 12 may containknowledge relating to the two “non-intelligent” field devices 1204 suchthat energy usage of the field devices 1204 may be approximated usingthe energy object 130 as a proxy. More specifically, the energy object130 located in the controller 120 may receive information that relatesto operation of the field devices 1204, such as measurements of currentand voltage, and may use knowledge related to the field devices 1204(which is stored in the energy object 130) to approximate the energyusage for the field devices 1204. In certain embodiments, thesemeasurements may also be transferred to the controller 120 or higherlevel energy management systems 140 via a different communicationprotocol than that which is used to communicate with the embedded energyobjects 130 in the intelligent field devices 1202. In another example,multiple field devices 1204 may be connected to the same energyconsuming or producing process 110, and each may measure a differentaspect of the energy consuming or producing process 110, for example, aflow and a temperature, respectively. Using this example, the energyobjects 130 in the controllers 120 or the higher level energy managementsystems 140 may combine the flow and temperature measurements toapproximate the energy usage.

In addition to using energy objects 130 located in higher level energymanagement systems 140 and controllers 120 as proxies for field devices1204, in certain embodiments, energy objects 130 located in intelligentfield devices 1202 may be used as proxies for other energy objects 130located in other intelligent field devices 1202. For example, FIG. 13 isa schematic block diagram of the system 1200 of FIG. 12 including anadditional intelligent field device 1202 that includes an energy object130 and controls an additional energy consuming or producing process110. In certain scenarios, the energy objects 130 located in one or bothof the intelligent field devices 1202 may not individually have all ofthe information necessary to determine the energy usage for theirrespective intelligent field device 1202. For example, perhaps oneprocess data value measured by a first intelligent field device 1202 maybe necessary to determine the energy usage of a second intelligent fielddevice 1202, which does not have direct access to that particularprocess data value. One example is a scenario where the firstintelligent field device 1202 receives information from pressuretransducers relating to pressures of a fluid flow through a compressor,pump, or other pressure increasing device, and the second intelligentfield device 1202 receives information from flow meters relating flowrates of the fluid flow. Individually, these two intelligent fielddevices 1202 may not be able to determine energy usage relating to theirrespective information (i.e., pressures and flows), but together the twointelligent field devices 1202 may be able to determine energy usagebased on calculations relating to the pressures and flows. As such, theenergy object 130 located in the first intelligent field device 1202 mayact as a proxy for the energy object 130 located in the secondintelligent field device 1202, or vice versa.

It should be noted that the energy objects 130 may serve numerouspurposes. However, in certain embodiments, the energy objects 130primarily serve two main purposes, namely making energy usagecalculations (i.e., monitoring) and initiating control actions (i.e.,control). In certain situations, the energy objects 130 may onlycalculate energy usage, and report the energy usage, for example.Conversely, in other situations, the energy objects 130 may onlyinitiate control actions. Furthermore, in yet other situations, theenergy objects 130 may calculate energy usage, and initial controlactions based on these energy calculations, among other things. In otherwords, depending on specific requirements, the energy objects 130 may beconfigured with appropriate attributes, messages, services, and soforth, to perform one, both, or none of these main purposes (i.e.,making energy usage calculations and initiating control actions).

Furthermore, the energy objects 130 of the system 1200 may be used toaggregate the energy usage calculations across the system 1200. Forexample, in certain embodiments, all of the energy objects 130throughout the system 1200 may report the energy usage calculations backto an aggregating energy object 130 in the higher level energymanagement system 140, where the individual energy usage calculationsare combined. The aggregated energy usage may represent the energy usedin a production line or a plant. In other embodiments, the energyobjects 130 may only report the energy usage calculations back to anaggregating energy object 130 in the controller 120 that is used tocontrol the components (e.g., the field devices 1202, 1204). The morelimited aggregated energy usage may represent the energy used in amachine or work cell.

Moreover, certain components (e.g., the intelligent field devices 1202,the controller(s) 120, and the higher level energy management system140) of the system 1200 may include software for creating visualizationsof the energy usage calculations that are calculated and/or aggregatedby the energy objects 130. In certain embodiments, the components mayinclude displays for displaying graphs, charts, tables, lists, and soforth, of the energy usage that is calculated and/or aggregated by theenergy objects 130 associated with that particular component. Forexample, the controller 120 illustrated in FIGS. 12 and 13 may includevisualization software, in addition to the energy object 130, stored oncomputer readable media of the controller 120, and a processor forexecuting the visual software and displaying the graphs, charts, tables,lists, and so forth, on a display connected to or integrated into thecontroller 120. FIG. 14 is a schematic diagram of the controller 120 ofFIGS. 12 and 13, illustrating a computer readable media 1400, on whichthe energy object 130 and the visualization software 1402 may be stored,and a processor 1404, which may be used to execute the visualizationsoftware 1402 for displaying the graphs, charts, tables, lists, and soforth, on a display 1406. Again, although illustrated as being acontroller 120 that includes the energy object 130, the computerreadable media 1400, the visualization software 1402, and the processor1404, any of the other components (e.g., the field devices 1202, 1204and the higher level energy management system 140) of the system 1200illustrated in FIGS. 12 and 13 may also include these features forenabling visualization of the energy usage that is calculated and/oraggregated by the energy object 130.

Furthermore, in additional to the visualization software 1402, thecontroller 120 (and, indeed, any of the components of the system 1200)may also include server software 1408 for receiving requests from usersusing remote devices 1410 (e.g., personal computers, portable devicessuch as cell phones, and so forth) relating to the energy usagecalculations of the energy object 130, generating responses (e.g., webpages, text messages, alerts, and so forth) to the requests from theremote users 1410, and transmitting the responses to the remote devices1410 via a network 1412 (e.g., a local area network (LAN), wide areanetwork (WAN), the internet, and so forth). For example, in certainembodiments, the responses generated by the server software 1408 may besimilar to the visualizations (e.g., graphs, charts, tables, lists, andso forth) created by the visualization software 1402. Indeed, in certainembodiments, the server software 1408 may be directly integrated withthe visualization software 1402. As such, the server software 1408 andthe visualization software 1402 enable additional diagnostics,visualization, and so forth, directly from the controller 120 (or anyother component of the system 1200 of FIGS. 12 and 13).

As discussed above, the components (e.g., the controller 120 in FIG. 14)may be capable of aggregating energy usage via the energy objects 130.As illustrated in FIG. 14, the controller 120 may include dataaggregation software 1414, which may aggregate energy usage data fromthe various energy objects 130 of the system 1200 of FIGS. 12 and 13.For example, the data aggregation software 1414 may be configured tocompile energy usage data, determine when duplicate data exists (andhandle this data accordingly), determine when certain data are missing,and so forth. In addition, in certain embodiments, the data aggregationsoftware 1414 may publish the aggregated energy usage data to the cloudfor cloud storage. For example, the aggregated energy usage data may bestored across a plurality of remote distributed storage devices acrossthe network 1412. As will be appreciated, the visualization software1402, the server software 1408, and the data aggregation software 1414may all be separate computer software modules as illustrated in FIG. 14,or may be integrated with each other. Furthermore, any given componentof the system 1200 of FIGS. 12 and 13 may include one, two, or all ofthe visualization software 1402, the server software 1408, and the dataaggregation software 1414.

In certain embodiments, the computer readable medium 1400 may alsoinclude abstract process control algorithms 1416 that may be utilized bythe processor 1404 to control the energy consuming or producingprocesses 110 by utilizing the field devices 1204 and intelligent fielddevices 1202, where the abstract process control algorithms 1416 utilizeenergy objects 130. The abstract process control algorithms 1416 areabstract in the respect that they execute without modification,regardless of whether an energy object 130 resides in an intelligentfield device 1202 or an energy object 130 resides in a controller 120 asa proxy for a non-intelligent field device 1204, where the intelligentand non-intelligent devices 1202, 1204 have the same control functions.It will be appreciated that the visualization software 1402 is alsoabstract with respect to rendering embedded energy objects 130 and proxyenergy objects 130. In fact, all software and firmware components of theautomation system that can utilize an embedded energy object 130 canutilize a proxy energy object 130 without algorithmic alteration.

In general, energy packets or objects can be utilized for variousapplications. These include methods for aggregating energy data,measuring each machine for analysis and comparison, and determiningenergy cost per product (e.g., by tagging a bill of material with objectdata). The objects enable bridging the gap between 1st and 2nd shiftsfor example and minimize energy costs. These include providing energyinformation for use with other factors, such as order backlog, laborcosts, and so forth. Line of sight controls include Level 1—basicmetering, Level 2—sub metering, and Level 3—integrated data/decisionforecasting.

The energy objects facilitate a proactive system that considers rawmaterials, physical assets/equipment, and production schedule for theuser including use by automated agents. The energy object can becombined with CIP protocol for real-time monitoring and control. Thisincludes determining regeneration opportunities within industrial driveand motion controllers. For example this includes control algorithms formechanical shift to allow powered drives/controllers to affect idledrives/controllers.

The energy object includes a framework and proxy for certainapplications including synchronized use of CIP objects across multiplefacilities to effectuate produce/consume energy decisions. This helpsusers identify opportunities to harness energy existing in the facilitywhich can include the use of gravity, motion on rollers, or transfer toflywheel or alternative fuel source (e.g., hybrid energy). The CIPenergy objects can be employed to intelligently communicate with activeand idled equipment to save costs. For example considering where robotsare idle so many hours per year or what conveyors and other applicationsare employed including “Just-in-time” power concepts. The object can beemployed as an entry point into the application and employed withsuppliers to compare products and improve products/equipment used infacility. As noted previously CIP energy objects can place devices into“safe” mode/state based on safety modes.

The CIP energy objects can also be used in facility optimization whereattributes of CIP energy objects include maximum and minimum values foreach device. Some example attributes include an identifier, a devicename, a hierarchy/fully qualified parameter, an object class, a role, atype of energy including water, gas, air steams, a measurementparameter, some type of aggregation, and some type of time reference.The energy objects can reside in various industrial automation hardwareor software configurations.

It is noted that the term energy as used herein can be broadly definedto include one or more sustainability factors that can also be employedwith the energy objects described herein. Sustainability factors can beassociated with the product, the process, or a combination. TheSustainability factors can be used to extend a) the specification ofmaterials and products b) the work instructions used to transform theproducts into finished material c) descriptors and other factorsassociated with the human resources performing production d) factorsassociated with the machines performing production e) factors associatedwith the facility and utilities supply chain involved in production,such as type of electricity used (solar vs. wind vs. coal, for example)and f) scheduling information. Sustainability factors can be createdusing known industry standards, or, individuals can develop their ownfactors in order to track and measure those characteristics that are ofparticular importance to them. However, as a sustainability factor couldbe self-created to account for factors unique in importance to anindividual, company, retailer, region, and so forth, thus, it is to beappreciated that is not an all-inclusive list. Thus, energy objects asdescribed herein can include monitoring and/or control of one or moresustainability factors. The following description provides some exampleprocesses where energy objects can be employed to monitor or controlsustainability factors.

In one aspect, energy objects can be employed for optimizing productionin view of detected carbon footprint ranges. In this aspect,sustainability factors are monitored and a decision is made as towhether or not current production methods are within an acceptable rangeto meet the desired carbon footprint. If the current range isacceptable, the process employs current production methods that satisfythe respective ranges. If the current production is not withinacceptable ranges, the process proceeds where ingredients may bealtered, shipping methods may be altered, and/or manufacturing methodsmay be altered to achieve desired carbon footprint levels. As notedpreviously, factors outside of the production process itself can impactthe ultimate cost and profitability of the end product. Production usingresources from various regions, or targeted for shipment to variousregions, can be automatically modified depending upon the acceptablerange of detected values for the carbon footprint of the end productwhich can be communicated and controlled via the energy objects. Thus,modeling can determine: which batch of raw ingredients or; whichmanufacturing method and/or; which shipping method provides the lowest(or suitable) overall carbon footprint for a particular product and/ordestination.

In another aspect, energy objects can be employed for optimizingprocurement and shipping systems in view of detected environmental orother energy/sustainability factors. Environmental factors areconsidered such as weather or other climate goals that may be desiredfor a particular product or process. Thus, it may be determined that aparticular location is cooler than projected thus a different type ofshipping or packaging could be employed. Procurement of supplies and/orproduction methods can be automatically adjusted in view of currentenvironmental data. Material or products can be purchased or transportedto support the environmental goals. As noted previously, shipments andadditional factors could be aligned with environmental factors such asweather, to minimize environmental impact. For example, by coordinatingwith weather systems, truck shipments in affected regions could bedelayed during ‘ozone alert’ times, or shifted to rail transport. Theoverall objective could be to optimize production while minimizingenvironmental impact. Advanced modeling could ascertain that undercertain conditions, high ozone days are likely to occur in an upcomingweek, and thus the manufacturer should pre-order those materials thatrequire truck shipments to avoid increasing the ozone impact. Similarly,by coordinating with weather systems, production and shipping could beoptimized to take advantage of ‘hotter’ or ‘colder’ routes for productsrequiring controlled storage, for example. The energy objects describedherein can be employed to provide such coordination and control.

In yet another aspect, energy objects can be employed for optimizingregulatory compliance in view of various sustainability factors.Regulatory rules can be determined for a destination location, forexample. These can include safety compliance, emissions, carbon taxes,in addition to other sustainability factors. Production requirements canbe determined in view of the rules and related sustainability factorsand optimized in view of the regulations. This can include manufacturingwith alternative energy sources in order to meet some incentive offeredby a regulating body. Labels can be automatically updated to reflectcompliance with regulations and sustainability factors. Data andprocesses from a sustainability optimization system could includeinterconnectivity with a database containing regulatory rules tosimplify regulatory decision making and oversight. For example, aparticular government authority may desire to encourage the use of solarpower. Merely having energy usage information on a label would beinsufficient to administer a tax on a product, as that would notindicate what type of energy was used. By associating a sustainabilityfactor indicating the type of energy used for production, in addition toother relevant sustainability factors, manufacturers could optimizeproduction to take maximum advantage of government rebates and otherincentives while minimizing the risk of adverse judgments. Similarly,regulatory bodies could optimize tax administration and administrationof other regulations to drive the desired behavior to keep theireconomies and environments responsible and sustainable.

As noted previously, discrete energy monitors can be stationedthroughout an industrial system or process and are employed to collectdata from various sustainable sources including produced or consumedenergy. The sustainable sources can be from various portions of aprocess and related to such factors as energy or waste for example. Atagging component such as a data historian (e.g., I/O module thatidentifies where/when energy is consumed) is provided to label or markthe collected source data as to which portion of an industrial processthe data is associated with. For example, in a batch process, the sourcedata may be tagged to indicate which pipe or valve a recipe componentwas transported across and how much energy such pipe or valve consumedas part of the process. From another point of view, the pipe or valvemay be attributed to the amount of waste associated with a portion ofthe batch process and in its own manner, reflect a type of energy orsustainability factor that is attributable to the respective process. Ina discrete process, where items may be assembled in a parallel or serialmanner, the sources may be tagged to indicate a sustainability factorfor the various components of the discrete process (e.g., discreteprocess A building an engine lists various components of the enginewhere the tagged data from the sources is associated with the enginecomponents). A processor or controller collects the tagged data andlinks the tagged data with a manufacturing model to produce a model orspecification that includes the discrete or batch process componentsthat have been associated with the respective sustainability factors orenergy source data. By associating energy or other sustainabilityfactors with the manufacturing model or specification, variousefficiencies can be provided for and managed within the factory sinceeach item's energy/sustainability component can now be accounted for andtraced as a component of the respective discrete or batch process.

In general, sustainable factors such as energy are monitored throughouta plant or process and associated with the model and energy object inorder to increase plant efficiencies. Automated monitors can receivedata from a plurality of sustainable sources that are distributed acrossan industrial process. Such processes can include discrete processeswhere automated assemblies occur (e.g., packaged assemblies) or caninclude batch processes where mixtures of various ingredients arecombined to form a recipe or other combination of elements (e.g.,chemical process, food process, beverage process, and so forth). As therespective processes are monitored, sustainable sources such as energythat is collected is tagged to indicate which portion of the discrete orbatch process that the source contributed to. After tagging, the data isassociated with the manufacturing model, where industrial managers orautomated processes can then analyze the process for the components ofenergy that were attributed to the various portions of the respectiveprocess.

In contrast to prior systems that could only view energy from theoverall sense of plant-wide consumptions, the source data that isassociated with the energy object can now be analyzed in real-time orvia offline modeling to optimize and mitigate energy usage. For example,portions of a process may be rearranged to minimize overall energy usage(e.g., perform step C before step A in order to conserve energy from thereverse order of A and C). It is noted that various models can haveassociated sustainable factors. Such models include MRP models (materialrequirement planning), MES models (manufacturing execution system), ERPmodels (enterprise resource planning), programming models (e.g., ladderlogic, SFC, batch program, function block), and so forth. In general,the energy objects aggregates energy or other consumption data from theplant floor and correlates it to production output. This enablesapplying standard production modeling tools for production energy andemission forecasting and optimization, while extending the existingfacility demand management system to include production, and lastly,link that system to the Demand Response and Smart Grid (DRSG), as wellas, Cap and Trade systems, for example.

In another aspect, an energy object extension to an industrial protocolhaving a comprehensive suite of attributes, messages and servicesutilized for the monitoring and control of energy consuming or producingresources by a manufacturing automation application is provided. Theenergy object includes an identifier associated with an energy resourcethat is associated with a manufacturing automation application and anenergy type associated with the energy resource. This includes ameasurement characteristic associated with the energy resource tofacilitate energy management by the manufacturing automationapplication. The industrial protocol is associated with a CommonIndustrial Protocol (CIP) that further comprises an Ethernet protocol, adevice protocol, a control protocol, or a Modbus protocol, for example.The energy object extension includes a demand and response applicationto activate or deactivate components to facilitate energy management.This can also include a safety component to activate or deactivatecomponents. The demand and response application is associated withreducing a base load, sequencing a start up, shedding non-criticalloads, generating power, storing energy for later use, staggering powerpeaks, or operating at a reduced rate or capacity and can also beassociated with a smart grid. This includes a manufacturing executionsystem (MES) or an energy management control system (EMCS) to facilitateenergy management.

In another aspect, a historian component is employed to generate theidentifier, energy type, or measurement characteristic. The energyobject extension includes an aggregation parameter, a role parameter, oran operational state parameter. This includes a units/scaling parameter,a roll over parameter, production capacity parameter, or a typeparameter. This also includes a time parameter, a data log parameter, ashed and produce service, or an alarm and event message. The energyobject extension also includes a parameter object to facilitateconfiguration, an energy object instance for a device, or aninput/output assembly object to facilitate control. This includes anenergy structured tag to facilitate energy control and an energy-enabledapplication that includes a device name, an energy state, a power graph,a demand charge, or an alarm. This can also include energy-enabled phaselogic to facilitate energy control in a process or a controller to setincreased energy modes of a system. The energy object extension includesa regulation service that exchanges energy to facilitate performance ofother components associated with a grid. This includes one or moresustainability sources that are employed to control energy resources,where the sustainability sources are associated with cap and tradepolicies, waste management activities, or maintenance activities.

In another aspect, a manufacturing automation system for monitoringenergy across multiple devices connected by one or more networks isprovided. This includes a control and information platform forautomatically increasing or decreasing energy resources of an automatedsystem; and an energy object having an identifier, an energy type, and ameasurement component to facilitate increasing or decreasing energyresources of the automation system.

In another aspect, a method to extend an industrial protocol having acomprehensive suite of attributes, messages and services formanufacturing automation applications related to energy production andconsumption is provided. This includes monitoring a plurality of energysources; associating the energy sources with a plurality of energyobjects; associating the energy sources with an industrial automationprotocol; and employing the industrial automation protocol todynamically increase or decrease energy demands across an automatedfactory environment. The energy object includes an identifier, ameasurement characteristic, an aggregation parameter, a role parameter,an operational state parameter, a units/scaling parameter, a roll overparameter, production capacity parameter, or a type parameter, a timeparameter, a data log parameter, a shed and produce service, or an alarmand event message.

It is noted that as used in this application, terms such as “component,”“module,” “system,” and the like are intended to refer to acomputer-related, electro-mechanical entity or both, either hardware, acombination of hardware and software, software, or software in executionas applied to an automation system for industrial control. For example,a component may be, but is not limited to being, a process running on aprocessor, a processor, an object, an executable, a thread of execution,a program and a computer. By way of illustration, both an applicationrunning on a server and the server can be components. One or morecomponents may reside within a process or thread of execution and acomponent may be localized on one computer or distributed between two ormore computers, industrial controllers, or modules communicatingtherewith.

The subject matter as described above includes various exemplaryaspects. However, it should be appreciated that it is not possible todescribe every conceivable component or methodology for purposes ofdescribing these aspects. One of ordinary skill in the art may recognizethat further combinations or permutations may be possible. Variousmethodologies or architectures may be employed to implement the subjectinvention, modifications, variations, or equivalents thereof.Accordingly, all such implementations of the aspects described hereinare intended to embrace the scope and spirit of subject claims.Furthermore, to the extent that the term “includes” is used in eitherthe detailed description or the claims, such term is intended to beinclusive in a manner similar to the term “comprising” as “comprising”is interpreted when employed as a transitional word in a claim.

While only certain features of the invention have been illustrated anddescribed herein, many modifications and changes will occur to thoseskilled in the art. It is, therefore, to be understood that the appendedclaims are intended to cover all such modifications and changes as fallwithin the true spirit of the invention.

The invention claimed is:
 1. An automation device, comprising: acomputer readable medium having software instructions encoded thereon,the software instructions comprising: an energy object associated withthe automation device and configured to: utilize attributes, messages,services, or any combination thereof, for monitoring and control of anenergy consuming or producing resource of an energy consuming orproducing process; calculate a first energy usage of the automationdevice; and act as a proxy for one or more other automation devices ofthe energy consuming or producing process by: calculating a secondenergy usage of the one or more other automation devices based on inputand output process data associated with the one or more other automationdevices and one or more relationships between the input and outputprocess data and the second energy usage, wherein the input and outputprocess data comprises a flow measurement, a temperature measurement, orany combination thereof associated with the one or more other automationdevices, and wherein the one or more relationships are stored locallywithin the energy object; determining one or more energy operationstates of the one or more other automation devices based on the secondenergy usage; and transmitting the one or more energy operation statesto the one or more other automation devices; and a processor configuredto execute the software instructions encoded on the computer readablemedium.
 2. The automation device of claim 1, wherein the energy objectis configured to calculate a third energy usage of the energy consumingor producing resource without communicating with another energy objectof another automation device of the energy consuming or producingprocess.
 3. The automation device of claim 1, wherein the energy objectis configured to calculate a third energy usage of the energy consumingor producing resource based on data received from another energy objectof another automation device of the energy consuming or producingprocess.
 4. The automation device of claim 1, wherein the softwareinstructions comprise visualization software for creating visualizationsof energy usage calculations performed by the energy object anddisplaying the visualizations on a display.
 5. The automation device ofclaim 4, wherein the display is configured to be directly integratedwith the automation device.
 6. The automation device of claim 1, whereinthe software instructions comprise server software for receiving arequest for information relating to a second energy usage of the energyconsuming or producing process from a remote device via a network,generating a response based on energy usage calculations performed bythe energy object, and transmitting the response to the remote devicevia the network.
 7. The automation device of claim 1, wherein thesoftware instructions comprise data aggregation software for aggregatingenergy usage data from energy usage calculations performed by the energyobject and other energy objects of the other automation devices of theenergy consuming or producing process.
 8. The automation device of claim7, wherein the data aggregation software is configured to publish theaggregated energy usage data to cloud storage.
 9. The automation deviceof claim 1, wherein the software instructions comprise a process controlalgorithm configured to utilize the first energy usage data, the secondenergy usage data, or any combination thereof from the energy object tocontrol the energy consuming or producing resource.
 10. The automationdevice of claim 1, wherein the automation device is a controller of theenergy consuming or producing process.
 11. The automation device ofclaim 1, wherein the energy object is configured to adjust the energyconsuming or producing process based on the second energy usage, theenergy operation state of the one or more other automation devices, orany combination thereof.
 12. An automation control system, comprising: afirst automation device configured to control a first energy consumingor producing process and comprising a computer readable medium havingsoftware instructions encoded thereon, the software instructionscomprising an energy object configured to utilize attributes, messages,services, or any combination thereof, for monitoring and control of anenergy consuming or producing resource of the first energy consuming orproducing process; and a second automation device configured to: controla second energy consuming or producing process; transmit input andoutput process data to the first automation device, wherein the energyobject is configured to perform energy usage calculations for the secondautomation device based on the input and output data and one or morerelationships between the input and output process data and energyusage, wherein the energy usage calculations are used to determine anenergy operation state of the second automation device, wherein theinput and output process data comprises a flow measurement, atemperature measurement, or any combination thereof associated with thesecond automation device and wherein the one or more relationships arestored locally within the object; wherein the second automation deviceis unable to perform the energy usage calculations; wherein the energyobject of the first automation device is configured to act as a proxyfor the second automation device by: receiving the data from the secondautomation device; performing the energy usage calculations based on thereceived data; determining the energy operation state of the secondautomation device based on the energy usage calculations; andtransmitting the energy operation state to the second automation device;and wherein the first automation device is configured to adjust thefirst energy consuming or producing process, the second energy consumingor producing process, or any combination thereof, based on the energyusage calculations, the energy operation state of the second automationdevice, or any combination thereof.
 13. The automation control system ofclaim 12, wherein the energy object of the first automation device isconfigured to calculate a second energy usage of the energy consuming orproducing resource based on the data received from the second automationdevice.
 14. The automation control system of claim 12, wherein thesoftware instructions of the first automation device comprisevisualization software for creating visualizations of energy usagecalculations performed by the energy object and displaying thevisualizations on a display.
 15. The automation control system of claim12, wherein the software instructions of the first automation devicecomprise server software for: receiving a request for informationrelating to a second energy usage of the second energy consuming orproducing process from a remote device via a network; generating aresponse based on the energy usage calculations performed by the energyobject; and transmitting the response to the remote device via thenetwork.
 16. The automation control system of claim 12, wherein thesoftware instructions of the first automation device comprise dataaggregation software for aggregating energy usage data from the energyusage calculations performed by the energy object.
 17. The automationcontrol system of claim 16, wherein the data aggregation software isconfigured to publish the aggregated energy usage data to cloud storage.18. A method, comprising: receiving data relating to a first energyconsuming or producing resource of an energy consuming or producingprocess using an energy object stored on a first automation device,wherein the energy object utilizes attributes, messages, services, orany combination thereof, for monitoring and controlling the first energyconsuming or producing resource; using the energy object as a proxy fora second automation device to: calculate energy usage of the secondautomation device based on input and output data relating to a secondenergy consuming or producing resource received from the secondautomation device and one or more relationships between the input andoutput process data and energy usage, wherein the input and outputprocess data comprises a flow measurement, a temperature measurement, orany combination thereof associated with the second automation device andwherein the one or more relationships are stored locally within theenergy object; determine an energy operation state of the secondautomation device based on the energy usage; and transmit the energyoperation state to the second automation device; and adjust the energyconsuming or producing process based on the energy usage, the energyoperation state of the second automation device, or any combinationthereof.
 19. The method of claim 18, comprising using visualizationsoftware stored on the first automation device to create visualizationsof energy usage calculations performed by the energy object, and todisplay the visualizations on a display.
 20. The method of claim 18,comprising using server software stored on the first automation deviceto: receive a request for information relating to a second energy usageof the energy consuming or producing process from a remote device via anetwork; generate a response based on energy usage calculationsperformed by the energy object; and transmit the response to the remotedevice via the network.
 21. The method of claim 18, comprising usingdata aggregation software stored on the first automation device toaggregate energy usage data from energy usage calculations performed bythe energy object and other energy objects of other automation devicesof the energy consuming or producing process.